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Erschienen in: European Radiology 2/2022

29.07.2021 | Oncology

MRI radiomics features of mesorectal fat can predict response to neoadjuvant chemoradiation therapy and tumor recurrence in patients with locally advanced rectal cancer

verfasst von: Vetri Sudar Jayaprakasam, Viktoriya Paroder, Peter Gibbs, Raazi Bajwa, Natalie Gangai, Ramon E. Sosa, Iva Petkovska, Jennifer S. Golia Pernicka, James Louis Fuqua III, David D. B. Bates, Martin R. Weiser, Andrea Cercek, Marc J. Gollub

Erschienen in: European Radiology | Ausgabe 2/2022

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Abstract

Objective

To interrogate the mesorectal fat using MRI radiomics feature analysis in order to predict clinical outcomes in patients with locally advanced rectal cancer.

Methods

This retrospective study included patients who underwent neoadjuvant chemoradiotherapy for locally advanced rectal cancer from 2009 to 2015. Three radiologists independently segmented mesorectal fat on baseline T2-weighted axial MRI. Radiomics features were extracted from segmented volumes and calculated using CERR software, with adaptive synthetic sampling being employed to combat large class imbalances. Outcome variables included pathologic complete response (pCR), local recurrence, distant recurrence, clinical T-category (cT), post-treatment T category (ypT), and post-treatment N category (ypN). A maximum of eight most important features were selected for model development using support vector machines and fivefold cross-validation to predict each outcome parameter via elastic net regularization. Diagnostic metrics of the final models were calculated, including sensitivity, specificity, PPV, NPV, accuracy, and AUC.

Results

The study included 236 patients (54 ± 12 years, 135 men). The AUC, sensitivity, specificity, PPV, NPV, and accuracy for each clinical outcome were as follows: for pCR, 0.89, 78.0%, 85.1%, 52.5%, 94.9%, 83.9%; for local recurrence, 0.79, 68.3%, 80.7%, 46.7%, 91.2%, 78.3%; for distant recurrence, 0.87, 80.0%, 88.4%, 58.3%, 95.6%, 87.0%; for cT, 0.80, 85.8%, 56.5%, 89.1%, 49.1%, 80.1%; for ypN, 0.74, 65.0%, 80.1%, 52.7%, 87.0%, 76.3%; and for ypT, 0.86, 81.3%, 84.2%, 96.4%, 46.4%, 81.8%.

Conclusion

Radiomics features of mesorectal fat can predict pathological complete response and local and distant recurrence, as well as post-treatment T and N categories.

Key Points

Mesorectal fat contains important prognostic information in patients with locally advanced rectal cancer (LARC).
Radiomics features of mesorectal fat were significantly different between those who achieved complete vs incomplete pathologic response (accuracy 83.9%, 95% CI: 78.6–88.4%).
Radiomics features of mesorectal fat were significantly different between those who did vs did not develop local or distant recurrence (accuracy 78.3%, 95% CI: 72.0–83.7% and 87.0%, 95% CI: 81.6–91.2% respectively).
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Literatur
1.
Zurück zum Zitat Horvat N, Petkovska I, Gollub MJ (2018) MR imaging of rectal cancer. Radiol Clin North Am 56:751–774CrossRef Horvat N, Petkovska I, Gollub MJ (2018) MR imaging of rectal cancer. Radiol Clin North Am 56:751–774CrossRef
2.
Zurück zum Zitat Nagtegaal ID, Quirke P (2008) What is the role for the circumferential margin in the modern treatment of rectal cancer? J Clin Oncol 26:303–312CrossRef Nagtegaal ID, Quirke P (2008) What is the role for the circumferential margin in the modern treatment of rectal cancer? J Clin Oncol 26:303–312CrossRef
3.
Zurück zum Zitat de Wilt JH, Vermaas M, Ferenschild FT, Verhoef C (2007) Management of locally advanced primary and recurrent rectal cancer. Clin Colon Rectal Surg 20:255–263CrossRef de Wilt JH, Vermaas M, Ferenschild FT, Verhoef C (2007) Management of locally advanced primary and recurrent rectal cancer. Clin Colon Rectal Surg 20:255–263CrossRef
5.
Zurück zum Zitat Horvat N, Veeraraghavan H, Khan M et al (2018) MR imaging of rectal cancer: radiomics analysis to assess treatment response after neoadjuvant therapy. Radiology 287:833–843CrossRef Horvat N, Veeraraghavan H, Khan M et al (2018) MR imaging of rectal cancer: radiomics analysis to assess treatment response after neoadjuvant therapy. Radiology 287:833–843CrossRef
6.
Zurück zum Zitat Zhou X, Yi Y, Liu Z et al (2020) Radiomics-based preoperative prediction of lymph node status following neoadjuvant therapy in locally advanced rectal cancer. Front Oncol 10:604CrossRef Zhou X, Yi Y, Liu Z et al (2020) Radiomics-based preoperative prediction of lymph node status following neoadjuvant therapy in locally advanced rectal cancer. Front Oncol 10:604CrossRef
7.
Zurück zum Zitat Zhang Y, He K, Guo Y et al (2020) A novel multimodal radiomics model for preoperative prediction of lymphovascular invasion in rectal cancer. Front Oncol 10:457CrossRef Zhang Y, He K, Guo Y et al (2020) A novel multimodal radiomics model for preoperative prediction of lymphovascular invasion in rectal cancer. Front Oncol 10:457CrossRef
8.
Zurück zum Zitat Liu M, Ma X, Shen F, Xia Y, Jia Y, Lu J (2020) MRI-based radiomics nomogram to predict synchronous liver metastasis in primary rectal cancer patients. Cancer Med 9:5155–5163CrossRef Liu M, Ma X, Shen F, Xia Y, Jia Y, Lu J (2020) MRI-based radiomics nomogram to predict synchronous liver metastasis in primary rectal cancer patients. Cancer Med 9:5155–5163CrossRef
9.
Zurück zum Zitat Varghese BA, Cen SY, Hwang DH, Duddalwar VA (2019) Texture analysis of imaging: what radiologists need to know. AJR Am J Roentgenol 212:520–528CrossRef Varghese BA, Cen SY, Hwang DH, Duddalwar VA (2019) Texture analysis of imaging: what radiologists need to know. AJR Am J Roentgenol 212:520–528CrossRef
10.
Zurück zum Zitat Lambin P, Leijenaar RTH, Deist TM et al (2017) Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol 14:749–762CrossRef Lambin P, Leijenaar RTH, Deist TM et al (2017) Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol 14:749–762CrossRef
11.
Zurück zum Zitat Petresc B, Lebovici A, Caraiani C, Feier DS, Graur F, Buruian MM (2020) Pre-treatment T2-WI based radiomics features for prediction of locally advanced rectal cancer non-response to neoadjuvant chemoradiotherapy: a preliminary study. Cancers (Basel) 12(7):1894 Petresc B, Lebovici A, Caraiani C, Feier DS, Graur F, Buruian MM (2020) Pre-treatment T2-WI based radiomics features for prediction of locally advanced rectal cancer non-response to neoadjuvant chemoradiotherapy: a preliminary study. Cancers (Basel) 12(7):1894
12.
Zurück zum Zitat Zhang XY, Wang L, Zhu HT et al (2020) Predicting rectal cancer response to neoadjuvant chemoradiotherapy using deep learning of diffusion kurtosis MRI. Radiology 296:56–64CrossRef Zhang XY, Wang L, Zhu HT et al (2020) Predicting rectal cancer response to neoadjuvant chemoradiotherapy using deep learning of diffusion kurtosis MRI. Radiology 296:56–64CrossRef
13.
Zurück zum Zitat Amor S, Iglesias-de la Cruz MC, Ferrero E et al (2016) Peritumoral adipose tissue as a source of inflammatory and angiogenic factors in colorectal cancer. Int J Colorectal Dis 31:365–375CrossRef Amor S, Iglesias-de la Cruz MC, Ferrero E et al (2016) Peritumoral adipose tissue as a source of inflammatory and angiogenic factors in colorectal cancer. Int J Colorectal Dis 31:365–375CrossRef
14.
Zurück zum Zitat Neto NIP, Murari ASP, Oyama LM et al (2018) Peritumoural adipose tissue pro-inflammatory cytokines are associated with tumoural growth factors in cancer cachexia patients. J Cachexia Sarcopenia Muscle 9:1101–1108CrossRef Neto NIP, Murari ASP, Oyama LM et al (2018) Peritumoural adipose tissue pro-inflammatory cytokines are associated with tumoural growth factors in cancer cachexia patients. J Cachexia Sarcopenia Muscle 9:1101–1108CrossRef
15.
Zurück zum Zitat Cao Y (2019) Adipocyte and lipid metabolism in cancer drug resistance. J Clin Invest 129:3006–3017CrossRef Cao Y (2019) Adipocyte and lipid metabolism in cancer drug resistance. J Clin Invest 129:3006–3017CrossRef
16.
Zurück zum Zitat Braman NM, Etesami M, Prasanna P et al (2017) Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI. Breast Cancer Res 19:57CrossRef Braman NM, Etesami M, Prasanna P et al (2017) Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI. Breast Cancer Res 19:57CrossRef
17.
Zurück zum Zitat Obeid JP, Stoyanova R, Kwon D et al (2017) Multiparametric evaluation of preoperative MRI in early stage breast cancer: prognostic impact of peri-tumoral fat. Clin Transl Oncol 19:211–218CrossRef Obeid JP, Stoyanova R, Kwon D et al (2017) Multiparametric evaluation of preoperative MRI in early stage breast cancer: prognostic impact of peri-tumoral fat. Clin Transl Oncol 19:211–218CrossRef
18.
Zurück zum Zitat Shaish H, Aukerman A, Vanguri R et al (2020) Radiomics of MRI for pretreatment prediction of pathologic complete response, tumor regression grade, and neoadjuvant rectal score in patients with locally advanced rectal cancer undergoing neoadjuvant chemoradiation: an international multicenter study. Eur Radiol. https://doi.org/10.1007/s00330-020-06968-6 Shaish H, Aukerman A, Vanguri R et al (2020) Radiomics of MRI for pretreatment prediction of pathologic complete response, tumor regression grade, and neoadjuvant rectal score in patients with locally advanced rectal cancer undergoing neoadjuvant chemoradiation: an international multicenter study. Eur Radiol. https://​doi.​org/​10.​1007/​s00330-020-06968-6
19.
Zurück zum Zitat Haller DG, Tabernero J, Maroun J et al (2011) Capecitabine plus oxaliplatin compared with fluorouracil and folinic acid as adjuvant therapy for stage III colon cancer. J Clin Oncol 29:1465–1471CrossRef Haller DG, Tabernero J, Maroun J et al (2011) Capecitabine plus oxaliplatin compared with fluorouracil and folinic acid as adjuvant therapy for stage III colon cancer. J Clin Oncol 29:1465–1471CrossRef
20.
Zurück zum Zitat Schmoll HJ, Twelves C, Sun W et al (2014) Effect of adjuvant capecitabine or fluorouracil, with or without oxaliplatin, on survival outcomes in stage III colon cancer and the effect of oxaliplatin on post-relapse survival: a pooled analysis of individual patient data from four randomised controlled trials. Lancet Oncol 15:1481–1492CrossRef Schmoll HJ, Twelves C, Sun W et al (2014) Effect of adjuvant capecitabine or fluorouracil, with or without oxaliplatin, on survival outcomes in stage III colon cancer and the effect of oxaliplatin on post-relapse survival: a pooled analysis of individual patient data from four randomised controlled trials. Lancet Oncol 15:1481–1492CrossRef
21.
Zurück zum Zitat Schmoll HJ, Tabernero J, Maroun J et al (2015) Capecitabine plus oxaliplatin compared with fluorouracil/folinic acid as adjuvant therapy for stage III colon cancer: final results of the NO16968 randomized controlled phase III trial. J Clin Oncol 33:3733–3740CrossRef Schmoll HJ, Tabernero J, Maroun J et al (2015) Capecitabine plus oxaliplatin compared with fluorouracil/folinic acid as adjuvant therapy for stage III colon cancer: final results of the NO16968 randomized controlled phase III trial. J Clin Oncol 33:3733–3740CrossRef
22.
Zurück zum Zitat Yothers G, O'Connell MJ, Allegra CJ et al (2011) Oxaliplatin as adjuvant therapy for colon cancer: updated results of NSABP C-07 trial, including survival and subset analyses. J Clin Oncol 29:3768–3774CrossRef Yothers G, O'Connell MJ, Allegra CJ et al (2011) Oxaliplatin as adjuvant therapy for colon cancer: updated results of NSABP C-07 trial, including survival and subset analyses. J Clin Oncol 29:3768–3774CrossRef
23.
24.
Zurück zum Zitat Zwanenburg A, Vallières M, Abdalah MA et al (2020) The Image Biomarker Standardization Initiative: standardized quantitative radiomics for high-throughput image-based phenotyping. Radiology 295(2):328–338 Zwanenburg A, Vallières M, Abdalah MA et al (2020) The Image Biomarker Standardization Initiative: standardized quantitative radiomics for high-throughput image-based phenotyping. Radiology 295(2):328–338
25.
Zurück zum Zitat Haibo He YB, Garcia EA, Shutao Li (2008) "ADASYN: adaptive synthetic sampling approach for imbalanced learning," 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), Hong Kong, pp 1322–1328. 13https://doi.org/10.1109/IJCNN.2008.4633969 Haibo He YB, Garcia EA, Shutao Li (2008) "ADASYN: adaptive synthetic sampling approach for imbalanced learning," 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), Hong Kong, pp 1322–1328. 13https://​doi.​org/​10.​1109/​IJCNN.​2008.​4633969
26.
Zurück zum Zitat Zoico E, Rizzatti V, Darra E et al (2017) Morphological and functional changes in the peritumoral adipose tissue of colorectal cancer patients. Obesity (Silver Spring) 25(Suppl 2):S87–S94 Zoico E, Rizzatti V, Darra E et al (2017) Morphological and functional changes in the peritumoral adipose tissue of colorectal cancer patients. Obesity (Silver Spring) 25(Suppl 2):S87–S94
27.
Zurück zum Zitat Haffa M, Holowatyj AN, Kratz M et al (2019) Transcriptome profiling of adipose tissue reveals depot-specific metabolic alterations among patients with colorectal cancer. J Clin Endocrinol Metab 104:5225–5237CrossRef Haffa M, Holowatyj AN, Kratz M et al (2019) Transcriptome profiling of adipose tissue reveals depot-specific metabolic alterations among patients with colorectal cancer. J Clin Endocrinol Metab 104:5225–5237CrossRef
28.
Zurück zum Zitat Kidd S, Spaeth E, Watson K et al (2012) Origins of the tumor microenvironment: quantitative assessment of adipose-derived and bone marrow-derived stroma. PLoS One 7:e30563CrossRef Kidd S, Spaeth E, Watson K et al (2012) Origins of the tumor microenvironment: quantitative assessment of adipose-derived and bone marrow-derived stroma. PLoS One 7:e30563CrossRef
29.
Zurück zum Zitat Dirat B, Bochet L, Dabek M et al (2011) Cancer-associated adipocytes exhibit an activated phenotype and contribute to breast cancer invasion. Cancer Res 71:2455–2465CrossRef Dirat B, Bochet L, Dabek M et al (2011) Cancer-associated adipocytes exhibit an activated phenotype and contribute to breast cancer invasion. Cancer Res 71:2455–2465CrossRef
30.
Zurück zum Zitat Duong MN, Geneste A, Fallone F, Li X, Dumontet C, Muller C (2017) The fat and the bad: mature adipocytes, key actors in tumor progression and resistance. Oncotarget 8:57622–57641CrossRef Duong MN, Geneste A, Fallone F, Li X, Dumontet C, Muller C (2017) The fat and the bad: mature adipocytes, key actors in tumor progression and resistance. Oncotarget 8:57622–57641CrossRef
31.
Zurück zum Zitat Jiramongkol Y, Lam EW (2020) Multifaceted oncogenic role of adipocytes in the tumour microenvironment. Adv Exp Med Biol 1219:125–142CrossRef Jiramongkol Y, Lam EW (2020) Multifaceted oncogenic role of adipocytes in the tumour microenvironment. Adv Exp Med Biol 1219:125–142CrossRef
32.
Zurück zum Zitat Bussard KM, Mutkus L, Stumpf K, Gomez-Manzano C, Marini FC (2016) Tumor-associated stromal cells as key contributors to the tumor microenvironment. Breast Cancer Res 18:84CrossRef Bussard KM, Mutkus L, Stumpf K, Gomez-Manzano C, Marini FC (2016) Tumor-associated stromal cells as key contributors to the tumor microenvironment. Breast Cancer Res 18:84CrossRef
33.
Zurück zum Zitat Gillies RJ, Kinahan PE, Hricak H (2016) Radiomics: images are more than pictures, they are data. Radiology 278:563–577CrossRef Gillies RJ, Kinahan PE, Hricak H (2016) Radiomics: images are more than pictures, they are data. Radiology 278:563–577CrossRef
34.
Zurück zum Zitat Petrelli F, Trevisan F, Cabiddu M et al (2020) Total neoadjuvant therapy in rectal cancer: a systematic review and meta-analysis of treatment outcomes. Ann Surg 271:440–448CrossRef Petrelli F, Trevisan F, Cabiddu M et al (2020) Total neoadjuvant therapy in rectal cancer: a systematic review and meta-analysis of treatment outcomes. Ann Surg 271:440–448CrossRef
Metadaten
Titel
MRI radiomics features of mesorectal fat can predict response to neoadjuvant chemoradiation therapy and tumor recurrence in patients with locally advanced rectal cancer
verfasst von
Vetri Sudar Jayaprakasam
Viktoriya Paroder
Peter Gibbs
Raazi Bajwa
Natalie Gangai
Ramon E. Sosa
Iva Petkovska
Jennifer S. Golia Pernicka
James Louis Fuqua III
David D. B. Bates
Martin R. Weiser
Andrea Cercek
Marc J. Gollub
Publikationsdatum
29.07.2021
Verlag
Springer Berlin Heidelberg
Erschienen in
European Radiology / Ausgabe 2/2022
Print ISSN: 0938-7994
Elektronische ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-021-08144-w

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